Paper
6 July 2015 Use of neural image analysis methods in the process to determine the dry matter content in the compost
D. Wojcieszak, J. Przybył, A. Lewicki, A. Ludwiczak, A. Przybylak, P. Boniecki, K. Koszela, M. Zaborowicz, K. Przybył, K. Witaszek
Author Affiliations +
Proceedings Volume 9631, Seventh International Conference on Digital Image Processing (ICDIP 2015); 963118 (2015) https://doi.org/10.1117/12.2197035
Event: Seventh International Conference on Digital Image Processing (ICDIP15), 2015, Los Angeles, United States
Abstract
The aim of this research was investigate the possibility of using methods of computer image analysis and artificial neural networks for to assess the amount of dry matter in the tested compost samples. The research lead to the conclusion that the neural image analysis may be a useful tool in determining the quantity of dry matter in the compost. Generated neural model may be the beginning of research into the use of neural image analysis assess the content of dry matter and other constituents of compost. The presented model RBF 19:19-2-1:1 characterized by test error 0.092189 may be more efficient.
© (2015) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
D. Wojcieszak, J. Przybył, A. Lewicki, A. Ludwiczak, A. Przybylak, P. Boniecki, K. Koszela, M. Zaborowicz, K. Przybył, and K. Witaszek "Use of neural image analysis methods in the process to determine the dry matter content in the compost", Proc. SPIE 9631, Seventh International Conference on Digital Image Processing (ICDIP 2015), 963118 (6 July 2015); https://doi.org/10.1117/12.2197035
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Cited by 14 scholarly publications.
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KEYWORDS
Image analysis

Image processing

Artificial neural networks

Analytical research

Mining

Agriculture

Error analysis

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